Search: “evaluation”

Towards Unconstrained Human-Object Interaction

arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.

researcharxiv-cs-cv

Training-Free Semantic Multi-Object Tracking with Vision-Language Models

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arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact

researcharxiv-cs-cv

16 Apr 2026

UNBOX: Unveiling Black-box visual models with Natural-language

arXiv:2603.08639v2 Announce Type: replace Abstract: Ensuring trustworthiness in open-world visual recognition requires models that are interpretable, fair, and robust to distribution shifts. Yet moder

UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes

model-releasesarxiv-cs-cv

arXiv:2511.23332v2 Announce Type: replace Abstract: Instruction-driven segmentation in remote sensing generates masks from guidance, offering great potential for accessible and generalizable applicati

UNRIO: Uncertainty-Aware Velocity Learning for Radar-Inertial Odometry

model-releasesarxiv-cs-ro

arXiv:2604.13584v1 Announce Type: new Abstract: We present UNRIO, an uncertainty-aware radar-inertial odometry system that estimates ego-velocity directly from raw mmWave radar IQ signals rather than

Unsupervised Anomaly Detection in Process-Complex Industrial Time Series: A Real-World Case Study

model-releasesarxiv-cs-lg

arXiv:2604.13928v1 Announce Type: new Abstract: Industrial time-series data from real production environments exhibits substantially higher complexity than commonly used benchmark datasets, primarily

VIGILant: an automatic classification pipeline for glitches in the Virgo detector

arXiv:2604.13687v1 Announce Type: cross Abstract: Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work in

researcharxiv-cs-lg

Vision-and-Language Navigation for UAVs: Progress, Challenges, and a Research Roadmap

arXiv:2604.13654v1 Announce Type: new Abstract: Vision-and-Language Navigation for Unmanned Aerial Vehicles (UAV-VLN) represents a pivotal challenge in embodied artificial intelligence, focused on ena

agentsarxiv-cs-ro

What Are We Really Measuring? Rethinking Dataset Bias in Web-Scale Natural Image Collections via Unsupervised Semantic Clustering

arXiv:2604.13610v1 Announce Type: new Abstract: In computer vision, a prevailing method for quantifying dataset bias is to train a model to distinguish between datasets. High classification accuracy i

When Less Latent Leads to Better Relay: Information-Preserving Compression for Latent Multi-Agent LLM Collaboration

arXiv:2604.13349v1 Announce Type: new Abstract: Communication in Large Language Model (LLM)-based multi-agent systems is moving beyond discrete tokens to preserve richer context. Recent work such as L

agentsarxiv-cs-lg

When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning?

model-releasesarxiv-cs-cl

arXiv:2503.23137v2 Announce Type: replace-cross Abstract: Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant c

ZoomSpec: A Physics-Guided Coarse-to-Fine Framework for Wideband Spectrum Sensing

arXiv:2604.13568v1 Announce Type: new Abstract: Wideband spectrum sensing for low-altitude monitoring is critical yet challenging due to heterogeneous protocols,large bandwidths, and non-stationary SN

applicationsarxiv-cs-cv

2/5 Turns out the model wasn't remembering the solution, but it was identifying 'gold-like' aesthetics like minimality & clarity. Total form…

model-releasesai21-labs--x

AI21 Labs shared findings indicating that their model does not simply memorize solutions but instead identifies and recognizes aesthetic qualities associated with high-quality outputs, such as minimal

A document is worth a structured record: Principled inductive bias design for document recognition

arXiv:2507.08458v2 Announce Type: replace-cross Abstract: Many document types use intrinsic, convention-driven structures that serve to encode precise and structured information, such as the conventio

safetyarxiv-cs-ai

A Geometric Algebra-informed NeRF Framework for Generalizable Wireless Channel Prediction

arXiv:2604.11983v1 Announce Type: cross Abstract: In this paper, we propose the geometric algebra-informed neural radiance fields (GAI-NeRF), a novel framework for wireless channel prediction that lev

applicationsarxiv-cs-lg

A Residual-Shell-Based Lower Bound for Ollivier-Ricci Curvature

arXiv:2604.12211v1 Announce Type: new Abstract: Ollivier-Ricci curvature (ORC), defined via the Wasserstein distance that captures rich geometric information, has received growing attention in both th

researcharxiv-cs-lg

A Scoping Review of Large Language Model-Based Pedagogical Agents

arXiv:2604.12253v1 Announce Type: new Abstract: This scoping review examines the emerging field of Large Language Model (LLM)-based pedagogical agents in educational settings. While traditional pedago

agentsarxiv-cs-ai

A Two-Stage LLM Framework for Accessible and Verified XAI Explanations

arXiv:2604.12543v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to translate the technical outputs of eXplainable Artificial Intelligence (XAI) methods into accessib

applicationsarxiv-cs-ai

A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model

arXiv:2405.04108v2 Announce Type: replace-cross Abstract: Recent booming development of Generative Artificial Intelligence (GenAI) has facilitated model commercialization to reinforce the model perfor

researcharxiv-cs-ai

AAPO: Enhancing the Reasoning Capabilities of LLMs with Advantage Margin

arXiv:2505.14264v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has emerged as an effective approach for enhancing the reasoning capabilities of large language models (LLMs), esp

AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought

arXiv:2501.16154v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on diverse corpora. Although these models sho

researcharxiv-cs-ai

Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning

arXiv:2505.17086v4 Announce Type: replace Abstract: Large Language Models (LLMs) equipped with modern Retrieval-Augmented Generation (RAG) systems often employ multi-turn interaction pipelines to inte

Local Ai

Agentic Control in Variational Language Models

arXiv:2604.12513v1 Announce Type: new Abstract: We study whether a variational language model can support a minimal and measurable form of agentic control grounded in its own internal evidence. Our mo

local-aiarxiv-cs-lg

Agentic Discovery with Active Hypothesis Exploration for Visual Recognition

arXiv:2604.12999v1 Announce Type: new Abstract: We introduce HypoExplore, an agentic framework that formulates neural architecture discovery for visual recognition as a hypothesis-driven scientific in

agentsarxiv-cs-cv

Agentic Insight Generation in VSM Simulations

arXiv:2604.12421v1 Announce Type: new Abstract: Extracting actionable insights from complex value stream map simulations can be challenging, time-consuming, and error-prone. Recent advances in large l

agentsarxiv-cs-cl

AGSC: Adaptive Granularity and Semantic Clustering for Uncertainty Quantification in Long-text Generation

arXiv:2604.06812v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated impressive capabilities in long-form generation, yet their application is hindered by the hallucinati

researcharxiv-cs-cl

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods

arXiv:2603.21011v2 Announce Type: replace-cross Abstract: Finite element (FE) analysis guides the design and verification of nearly all manufactured objects. It is at the core of computational enginee

agentsarxiv-cs-ai

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding

arXiv:2604.12335v1 Announce Type: new Abstract: Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as object coun

applicationsarxiv-cs-cv

Asymptotically Stable Gait Generation and Instantaneous Walkability Determination for Planar Almost Linear Biped with Knees

arXiv:2604.12274v1 Announce Type: new Abstract: A class of planar bipedal robots with unique mechanical properties has been proposed, where all links are balanced around the hip joint, preventing natu

researcharxiv-cs-ro

Audio Source Separation in Reverberant Environments using eta-divergence based Nonnegative Factorization

arXiv:2604.12480v1 Announce Type: cross Abstract: In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral

researcharxiv-cs-ai

Beyond Relevance: On the Relationship Between Retrieval and RAG Information Coverage

arXiv:2603.08819v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems combine document retrieval with a generative model to address complex information seeking tasks l

BID-LoRA: A Parameter-Efficient Framework for Continual Learning and Unlearning

arXiv:2604.12686v1 Announce Type: cross Abstract: Recent advances in deep learning underscore the need for systems that can not only acquire new knowledge through Continual Learning (CL) but also remo

Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem

arXiv:2604.13013v1 Announce Type: new Abstract: This paper tackles the Electric Capacitated Vehicle Routing Problem (E-CVRP) through a bilevel optimization framework that handles routing and charging

Local Ai

BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams

arXiv:2604.11861v1 Announce Type: new Abstract: Accurate and continuous localization of Autonomous Underwater Vehicles (AUVs) in GPS-denied environments is a persistent challenge in marine robotics. I

local-aiarxiv-cs-ro

BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands

arXiv:2511.22364v2 Announce Type: replace-cross Abstract: Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their worl

applicationsarxiv-cs-ai

BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities

arXiv:2603.27552v2 Announce Type: replace Abstract: Multimodal federated learning (FL) is essential for real-world applications such as autonomous systems and healthcare, where data is distributed acr

agentsarxiv-cs-lg

Boosting Visual Instruction Tuning with Self-Supervised Guidance

arXiv:2604.12966v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) perform well on many vision-language tasks but often struggle with vision-centric problems that require fine-gr

researcharxiv-cs-cv

Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining

arXiv:2604.12683v1 Announce Type: new Abstract: Current fMRI foundation models primarily rely on a limited range of brain states and mismatched pretraining tasks, restricting their ability to learn ge

Challenging Vision-Language Models with Physically Deployable Multimodal Semantic Lighting Attacks

arXiv:2604.12833v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable performance, yet their security remains insufficiently understood. Existing adversarial studies focu

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To

applicationsarxiv-cs-cl

CLAD: Efficient Log Anomaly Detection Directly on Compressed Representations

arXiv:2604.13024v1 Announce Type: new Abstract: The explosive growth of system logs makes streaming compression essential, yet existing log anomaly detection (LAD) methods incur severe pre-processing

researcharxiv-cs-lg

Clustering with Uniformity- and Neighbor-Based Random Geometric Graphs

model-releasesarxiv-cs-lg

arXiv:2501.06268v3 Announce Type: replace Abstract: We propose a graph-based clustering method based on Cluster Catch Digraphs (CCDs) that extends their applicability to moderate-dimensional data sett

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference

arXiv:2604.12913v1 Announce Type: cross Abstract: Binary decompilation is a critical reverse engineering task aimed at reconstructing high-level source code from stripped executables. Although Large L

Comparison of low Steps, Klein 9b x Z image turbo x Ernie Turbo x Qwen 2512 8 Steps

model-releasesr-stablediffusion

This r/StableDiffusion post presents a community-driven visual comparison of several modern, fast text-to-image diffusion models — Flux.2 Klein 9B (a smaller, faster distillation of Flux.2 Dev availab

Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors

arXiv:2604.12359v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) are increasingly deployed in real-world pipelines, yet this deployment also enlarges the supply-chain atta

Local Ai

Complex & Weird Prompt Test: ERNIE Turbo | Flux.2 Klein 4B | Z-Image Turbo

local-air-stablediffusion

This r/StableDiffusion post presents a community benchmark testing how three compact, fast AI image generation models — ERNIE Turbo, Flux.2 Klein 4B, and Z-Image Turbo — handle complex and unconventio

ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance

arXiv:2604.12308v1 Announce Type: new Abstract: Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires

Continuous Knowledge Metabolism: Generating Scientific Hypotheses from Evolving Literature

arXiv:2604.12243v1 Announce Type: cross Abstract: Scientific hypothesis generation requires tracking how knowledge evolves, not just what is currently known. We introduce Continuous Knowledge Metaboli

safetyarxiv-cs-ai